Maps of random walks on complex networks reveal community structure

Map of science
Map of science

Martin Rosvall and Carl T. Bergstrom

To comprehend the multipartite organization of large-scale biological and social systems, we introduce a new information-theoretic approach to reveal community structure in weighted and directed networks. The method decomposes a network into modules by optimally compressing a description of information flows on the network. The result is a map that both simplifies and highlights the regularities in the structure and their relationships to each other. We illustrate the method by making a map of scientific communication as captured in the citation patterns of more than 6000 journals. We discover a multicentric organization with fields that vary dramatically in size and degree of integration into the network of science. Along the backbone of the network — which includes physics, chemistry, molecular biology, and medicine — information flows bidirectionally, but the map reveals a directional pattern of citation from the applied fields to the basic sciences.

PNAS 105, 1118 (2008)

Code for the community-detection algorithm Infomap, Infomap online, and interactive applications for generating network maps, exploring networksvisualizing changes in networks and explaining the machinery of  the map equation for standard, multilevel, and higher-order networks are available on


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